E-Book Overview
Markov chains have increasingly become a useful way of capturing the stochastic nature of many economic and financial variables. Although the hidden Markov processes have been widely employed for some time in many engineering applications e.g. speech recognition, its effectiveness has now been recognized in areas of social science research as well. The main aim of Hidden Markov Models: Applications to Financial Economics is to make such techniques available to more researchers in financial economics. As such we only cover the necessary theoretical aspects in each chapter while focusing on real life applications using contemporary data mainly from the OECD group of countries. The underlying assumption here is that the researchers in financial economics would be familiar with such application although empirical techniques would be more traditional econometrics. Keeping the application level on a more familiar level, we focus on the methodology based on hidden Markov processes. This will, we believe, help the reader to develop a more in-depth understanding of the modeling issues, thereby benefiting their future research.
E-Book Content
Hidden Markov Models Advanced Studies in Theoretical and Applied Econometrics Volume 40 Managing Editor: J. Marquez, The Federal Reserve Board, Washington, D.C., U.S.A. Editorial Board: F.G. Adams, University of Pennsylvania, Philadelphia, U.S.A. P. Balestra, University of Geneva, Switzerland M.G. Dagenais, University of Montreal, Canada D. Kendrick, University of Texas, Austin, U.S.A. J.H.P. Paelinck, Netherlands Economic Institute, Rotterdam, The Netherlands R.S. Pindyck, Sloane School of Management, M.I.T., U.S.A. H. Theil, University of Florida, Gainesville, U.S.A. W. Welfe, University of Lodz, Poland The titles published in this series are listed at the end of this volume. Hidden Markov Models Ap